87 percent of organizations use network traffic analysis (NTA) tools for threat detection and response according to ESG, an IT strategy firm. In their 2020 study, 43 percent of organizations surveyed said NTA is a “first line of defense” for detecting and responding to threats.
Network detection and response, or NDR, has been established as a key tool for companies seeking to improve their threat response. It has become a network security strategy which developed in response to perceived shortcomings in existing network security systems.
MixMode announced today their inclusion in the 2021 Gartner report, ‘Emerging Trends: Top Use Cases for Network Detection and Response.’ The report, available only to Gartner users, provides in depth analysis on the top four use cases driving the NDR market including detection, hunting, forensics and response, as well as NDR development recommendations for product leaders.
We recently released a new video to better explain how MixMode’s next-generation cybersecurity anomaly detection platform combines the functionality of SIEM, NDR, NTA and UEBA for advanced threat detection, zero day attack identification, false positive alert reduction, forensic investigation and more.
Despite its inherent flaws, today’s SIEM software solutions still shine when it comes to searching and investigating log data. One effective, comprehensive approach to network security pairs the best parts of SIEM with modern, AI-driven predictive analysis tools. Alternatively, organizations can replace their outdated SIEM with a modern single platform self-learning AI solution.
When it comes to advancements in cybersecurity, rule-based systems are holding the industry back. Relying on humans to constantly input and label rules in order to detect and stay ahead of threats is a bottleneck process that is setting security teams up for failure, especially with tools like SIEM, NDR, and NTA.
MixMode creates a generative baseline. Unlike the historically-based baselines provided by add-on NTA solutions, a generative baseline is predictive, real-time, and accurate. MixMode provides anomaly detection and behavioral analytics and the ability to suppress false positives and surface true positives.
Most SIEM vendors acknowledge the value of network traffic data for leading indicators of attacks, anomaly detection, and user behavior analysis as being far more useful than log data. Ironically, network traffic data is often expressly excluded from SIEM deployments, because the data ingest significantly increases the required data aggregation and storage costs typically 3-5x.
One of the most prevalent issues impacting the effectiveness of security teams who use SIEM as their primary means of threat detection and remediation is the fact that data logs are an attractive medium for modern hackers to exploit.
Traditional security vendors offering solutions like SIEM (Security Information and Event Management) are overpromising on analytics while also requiring massive spend on basic log storage, incremental analytics, maintenance costs, and supporting resources.
Recently, network detection and response, or NDR, has been established as a key tool for companies seeking to improve their threat response. It’s a relatively new network security strategy which developed in response to perceived shortcomings in existing network security systems. We wanted to help explain what modern network detection and response is, how it …
What is Network Detection and Response (NDR)? A beginner’s Guide Read More →
Why Managed Service Providers should consider focusing on cybersecurity and how to build the tech stack for your new MSSP practice.
